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This article presents a critical review of the existing methodologies for process mathematical modelling in the area of wastewater engineering. It is argued that model identifiability is not a major i...
This paper describes an exploration in using SVM (Support Vector Machine) models, which were initially developed in the Machine Learning community, in flood forecasting, with the focus on the identifi...
The spatial interpolation of hydrometeorological data aims at estimating the value of rainfall at a given site based on the observation at neighboring stations. This is a problem of operational hydr...
The development of appropriate public policy responses to the impact of climate change on the overall ecosystem would require knowledge of future trends in the natural processes affecting the ecosyste...
This study seeks to identify sensitivity tools that will advance our understanding of lumped hydrologic models for the purposes of model improvement, calibration efficiency and improved measurement sc...
This article identifies different stakeholder perspectives on future flood management in the downstream parts of the Rhine basin in Germany and The Netherlands. The perspectives were identified using ...
The reduction of information contained in model time series through the use of aggregating statistical performance measures is very high compared to the amount of information that one would like to dr...
Flood frequency analysis typically assumes that annual floods arise from a single distribution and are independent. However, there is significant evidence for the existence of persistent climate modes...
Hidden Markov models (HMMs) can allow for the varying wet and dry cycles in the climate without the need to simulate supplementary climate variables. The fitting of a parametric HMM relies upon assump...
The rapidly growing demand for river flow data has increased pressure on hydrometric monitoring programmes to match a wide range of application-focused information needs, in particular, the identifica...

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